An Experimental Validation of the Polynomial Curvature Model: Identification and Optimal Control of a Soft Underwater Tentacle

Francesco Stella, Nana Obayashi, Cosimo Della Santina, Josie Hughes

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

The control possibilities for soft robots have long been hindered by the lack of accurate yet computationally treatable dynamic models of soft structures. Polynomial curvature models propose a solution to this quest for continuum slender structures. Nevertheless, the results produced with this class of models have been so far essentially theoretical. With the present work, we aim to provide a much-needed experimental validation to these recent theories. To this end, we focus on soft tentacles immersed in water. First, we propose an extension of the affine curvature model to underwater structures, considering the drag forces arising from the fluid-solid interaction. Then, we extensively test the model's capability to describe the system behavior across several shapes and working conditions. Finally, we validate model-based control policies, proposing and solving an optimal control problem for directional underwater swimming. Using the model we show an average increase of more than 3.5 times the swimming speed of a sinusoidal baseline controller, with some tentacles showing an improvement in excess of 5.5 times the baseline.

Original languageEnglish
Pages (from-to)11410-11417
Number of pages8
JournalIEEE Robotics and Automation Letters
Volume7
Issue number4
DOIs
StatePublished - 1 Oct 2022
Externally publishedYes

Keywords

  • Modeling, control, and learning for soft robots
  • flexible robotics
  • system identification

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